Tim Good
Impact in
- Hardware and Architecture top 5%
- Physical Unclonable Functions (PUFs) and Hardware Security
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- Chaos-based Image/Signal Encryption
Papers in
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- Cryptographic Implementations and Security 7
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- Neuroscience and Neural Engineering 6
- Co-authors
- Mohammed Benaissa (12 shared papers)Ben Heller (8 shared papers)Anthony T. Barker (6 shared papers)Mohammad R. Eissa (5 shared papers)David Howard (5 shared papers)Daisy Elliott (3 shared papers)Laurence Kenney (5 shared papers)Hui Zheng (3 shared papers)
- Journals
- IEEE Journal of Biomedical and Health Informatics (2 papers)Diabetic Medicine (1 paper)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)Archives of Physical Medicine and Rehabilitation (1 paper)BMC Neurology (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
Tim Good
24 papers receiving 547 citations
Peers
Comparison fields: 5 of 67
- Hardware and Architecture 132
- Computer Vision and Pattern Recognition 237
- Artificial Intelligence 350
- Health Information Management 33
- Rehabilitation 34
Countries citing papers authored by Tim Good
This map shows the geographic impact of Tim Good's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tim Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Good more than expected).
Fields of papers citing papers by Tim Good
This network shows the impact of papers produced by Tim Good. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tim Good. The network helps show where Tim Good may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Good, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 174 | |
| 2 | 2006 | 80 | |
| 3 | 2009 | 49 | |
| 4 | 2012 | 49 | |
| 5 | 2007 | 45 | |
| 6 | 2020 | 37 | |
| 7 | 2011 | 25 | |
| 8 | 2008 | 22 | |
| 9 | 2014 | 19 | |
| 10 | 2014 | 19 | |
| 11 | A deep neural network application for improved prediction of HbA1c in type 1 diabetes | 2020 | 9 |
| 12 | 2016 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2020 | 7 | |
| 15 | 2010 | 6 | |
| 16 | 2012 | 6 | |
| 17 | 2009 | 5 | |
| 18 | 2015 | 5 | |
| 19 | 2006 | 4 | |
| 20 | 1985 | 4 |
About Tim Good
Tim Good is a scholar working on Artificial Intelligence, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism and Biomedical Engineering, having authored 25 papers that have together received 587 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (7 papers), Neuroscience and Neural Engineering (6 papers), Chaos-based Image/Signal Encryption (6 papers), Diabetes Management and Research (5 papers), Physical Unclonable Functions (PUFs) and Hardware Security (5 papers), Muscle activation and electromyography studies (5 papers), RFID technology advancements (3 papers) and EEG and Brain-Computer Interfaces (3 papers). The work is most often cited by research in Hardware and Architecture (132 citations), Computer Vision and Pattern Recognition (237 citations), Artificial Intelligence (350 citations), Health Information Management (33 citations) and Rehabilitation (34 citations). Tim Good has collaborated with scholars based in United Kingdom. Frequent co-authors include Mohammed Benaissa, Ben Heller, Anthony T. Barker, Mohammad R. Eissa, David Howard, Daisy Elliott, Laurence Kenney, Hui Zheng, Glen Cooper and Timothy J. Healey. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Diabetic Medicine, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Archives of Physical Medicine and Rehabilitation and BMC Neurology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.